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Cell Segmentation datasets
archive 2025-07-28
22 datasets carry the task tag "Cell Segmentation" (the task itself: Cell Segmentation), ordered by the archive's paper count. Page 1 of 1: 22 shown of 22. Facet routes are this site's own (the archive records the tag string, not a page).
The archive holds 12,214 dataset rows; 12,172 are listed. 6 are withheld from every listing and count here as vandalised before snapshot (6 with contact-centre spam in the title, 0 with a spam description on a row that has no homepage, no paper and no papers counted; none with more than 1 paper, 0 with a benchmark), listed in withheld.json; 1 listed row carries a vandalised description, withheld on its page. This gate never withholds a row with a homepage or a paper that resolves, and a clean description; the content rules below withhold a row whose name is spam whatever else it carries. The gate is a phrase list: these are the rows it caught, not a claim that the rest is clean. Before that gate, the site's content rules withhold 36 more rows (invite-code, gambling, travel-booking, contact-centre and similar spam in the name or on a row with nothing real behind it); they have no page and are listed in withheld.json.
Filter 51 task tags shown of 3,717, by dataset count; the full filter by modality, task and language is on /datasets
Cell Segmentation datasets 1–22 of 22
STARE (Structured Analysis of the Retina)
The STARE (Structured Analysis of the Retina) dataset is a dataset for retinal vessel segmentation.
146 papers · 6 benchmarks
CoNSeP (Colorectal Nuclear Segmentation and Phenotypes)
The colorectal nuclear segmentation and phenotypes (CoNSeP) dataset consists of 41 H&E stained image tiles, each of size 1,000×1,000 pixels at 40× objective magnification.
68 papers · 2 benchmarks
PanNuke is a semi automatically generated nuclei instance segmentation and classification dataset with exhaustive nuclei labels across 19 different tissue types.
61 papers · 4 benchmarks
LIVECell (Label-free In Vitro image Examples of Cells)
The LIVECell (Label-free In Vitro image Examples of Cells) dataset is a large-scale microscopic image dataset for instance-segmentation of individual cells in 2D cell cultures.
18 papers · 1 benchmark
The dataset for this challenge was obtained by carefully annotating tissue images of several patients with tumors of different organs and who were diagnosed at multiple hospitals.
17 papers · 2 benchmarks
GFP-GOWT1 mouse stem cells Dr.
3 papers · 2 benchmarks
HeLa cells stably expressing H2b-GFP Mitocheck Consortium
3 papers · 2 benchmarks
The archive contains original images from U2OS cells stained with Hoechst 33342 as PNG files.
3 papers · 0 benchmarks
Deep learning use for quantitative image analysis is exponentially increasing.
2 papers · 1 benchmark
The archive contains original images from NIH3T3 cells stained with Hoechst 33342 as PNG files.
2 papers · 0 benchmarks
Glioblastoma-astrocytoma U373 cells on a polyacrylamide substrate Dr.
2 papers · 2 benchmarks
ACCT Data Repository (ACCT is a fast and accessible automatic cell counting tool using machine learning for 2D image segmentation)
This dataset is a collection of fluorescent images from mice in order to test an automatic cell counting tool that we developed.
1 paper · 0 benchmarks
HeLa cells on a flat glass Dr.
1 paper · 1 benchmark
MDA231 human breast carcinoma cells infected with a pMSCV vector including the GFP sequence, embedded in a collagen matrix Dr.
1 paper · 1 benchmark
Simulated nuclei of HL60 cells stained with Hoescht Dr.
1 paper · 1 benchmark
TYC Dataset (The TYC Dataset for Understanding Instance-Level Semantics and Motions of Cells in Microstructures)
We introduce the trapped yeast cell (TYC) dataset, a novel dataset for understanding instance-level semantics and motions of cells in microstructures.
1 paper · 0 benchmarks
An instance segmentation dataset of yeast cells in microstructures.
1 paper · 0 benchmarks
Microscopy is a cornerstone of biomedical research, enabling detailed study of biological structures at multiple scales.
1 paper · 0 benchmarks
ALFI (Annotations for Label-Free Images)
ALFI (Annotations for Label-Free Images) is a dataset of images and annotations for label-free microscopy imaging.
0 papers · 0 benchmarks
Simulated GFP-actin-stained A549 Lung Cancer cells embedded in a Matrigel matrix Dr.
0 papers · 0 benchmarks
Developing Tribolium Castaneum embryo (3D cartographic projection) Dr.
0 papers · 0 benchmarks
Paper counts and descriptions are the archive's, frozen 2025-07-28; no citation counts, no stars, no trending. Sorting by "most cited" or "newest" was a live-site feature the archive does not carry.